CN110095115A - A kind of carrier navigation attitude measurement method updated based on Geomagnetism Information - Google Patents
A kind of carrier navigation attitude measurement method updated based on Geomagnetism Information Download PDFInfo
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- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
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- G01C21/06—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by terrestrial means involving measuring of drift angle; involving correction for drift
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Abstract
The present invention relates to a kind of carrier navigation attitude measurement methods updated based on Geomagnetism Information comprising following steps: initialization；The calculating of magnetic declination；The data acquisition of subsequent time；The measurement of subsequent time navigation attitude information；The update of magnetic biasing angle information；Measurement method continuously carries out.The present invention is based on accelerometer, gyroscope and Magnetic Sensor measurement data, utilize the Kalman filtering algorithm of discretization, real-time estimation and update magnetic biasing angle information, the presence for avoiding the ferrimagnets such as magnetic mineral, reinforcing bar lead to the distortion of course angle information and unreliable problem caused by magnetic declination variation.
Description
Technical field
The present invention relates to carrier navigation attitude field of measuring technique, a kind of specifically carrier updated based on Geomagnetism Information
Navigation attitude measurement method.
Background technique
Navigation attitude measurement method refers to measurement course angle ψ, pitching angle theta and roll angleMethod.It is measured according to course angle ψ
Principle is different, and navigation attitude measurement method mainly has at present: astronomical surveing method, satellite navigation measurement method, inertial measurement method and
Magnetic survey method.
Astronomical observation system utilizes the measurement to celestial body to realize that navigation attitude information exports, and is affected by atmospheric effects big, environmental suitability
Difference.Satellite navigation measurement method is based on satellite navigation system location technology, measures course and pitch angle or three using double antenna
Antenna resolves navigation attitude, since antenna mounting locations error, presence of depth displacement etc. influence, can reduce its precision, and general precision
It is improved with the lengthening of baseline, is unsuitable for using on small-size equipment；Satellite data output frequency is usually no more than 10Hz,
Response speed is slower, can not provide high frequency or real-time navigation attitude information；It is defended in addition, satellite navigation measurement method needs to receive navigation
The characteristics of star signal determines it, and the following limitations exist: (1) signal is weak, is easy to be interfered and cheat；(2) due to decaying
It is seriously difficult to reach indoor, jungle and underwater and ground；(3) there is the danger attacked in navigation satellite.Inertial measurement method
High-precision inertia device is relied on, i.e., earth rotation method is perceived by high-precision day gyroscope, realizes course angle observation, body
Product is big, at high cost, it usually needs a large amount of peripheral circuits are integrated, and the above disadvantage greatly limits it in more areas
Application, especially to more demanding civil fields such as inexpensive small size lightweights.
Magnetic survey method, which refers to, makes full use of the ubiquitous directive earth's magnetic field of tool on the earth, by measuring magnetic
The north is in conjunction with angle, that is, magnetic declination between magnetic north and geographical north, acquisition navigation attitude information.It is surveyed with astronomical surveing method, inertia
Amount method and satellite navigation measurement method are compared, and magnetic survey method has environmental suitability strong, at low cost, passive, autonomous
Etc. advantages.Navigation attitude measurement method based on Geomagnetism Information mainly has geomagnetic matching, earth magnetism filtering and electronic compass three classes at present
Mode.Geomagnetic matching and earth magnetism filter both modes and are dependent on pre-stored accurately magnetic chart.However, earth's magnetic field is wrapped
Containing complicated and changeable, it is difficult to which predicted anomaly field, accurately magnetic chart is often difficult to obtain；Especially near surface region, anomalous field
Influence more feel that the use for the navigation attitude measurement method for obviously causing geomagnetic matching and earth magnetism to filter is restricted.
The mode of this measurement navigation attitude of electronic compass does not need accurately magnetic chart, often utilizes magnetic declination certain
Change little, approximate constant characteristic in zone aspect, obtains course angle ψ information；Meanwhile it being perceived using accelerometer
Gravity field information realizes pitching angle theta and roll angle φ measurement, realizes the pose compensation of course angle ψ measurement process.Carrier is transported
During dynamic, carrier acceleration interferes gravitational field infomation detection, usually introduces micro electronmechanical (MEMS) gyroscope, and adopt
With filtering algorithm, to realize that the navigation attitude in dynamic process measures.However, the variation such as magnetic mineral of extraneous magnetic environment, containing reinforcing bar
Etc. the presence of ferromagnetic building, all magnetic declination can be caused to change, the course angle that electronic compass mode obtains can be distorted
Information.
So how the real-time update based on Geomagnetism Information, realize to the real time calibration of magnetic declination, it is accurate to carry out navigation attitude survey
Amount method carries out becoming technical problem urgently to be solved.
Summary of the invention
The purpose of the present invention is to solve extraneous magnetic environments in the prior art, and magnetic biasing angular defect is provided one kind and is based on
The carrier navigation attitude measurement method that Geomagnetism Information updates solves the above problems.
To achieve the goals above, technical scheme is as follows:
A kind of carrier navigation attitude measurement method updated based on Geomagnetism Information, comprising the following steps:
Initialization: the pitching angle theta of current time t=k is obtainedk, roll angleWith course angle ψkInformation；
The calculating of magnetic declination: it using the Magnetic Sensor metric data of current time t=k, resolves and measures magnetic heading angle αm,k；
According to the course angle ψ at current timekWith measurement magnetic heading angle αm,k, calculate declination Dk, calculation formula is as follows:
Dk=ψk-αm,k；
The data acquisition of subsequent time: the accelerometer of subsequent time t=k+1, the amount of gyroscope and Magnetic Sensor are obtained
Measured data；
The measurement of subsequent time navigation attitude information: resolve subsequent time t=k+1's using discretization kalman filter method
Pitching angle thetak+1, roll angleWith course angle ψk+1And measure magnetic heading angle αm,k+1；
The update of magnetic biasing angle information: according to the course angle ψ of subsequent time t=k+1k+1With measurement magnetic heading angle αm,k+1, more
Declination D when new subsequent time t=k+1k+1；
Measurement method continuously carries out: returning to the data acquisition step of subsequent time, obtains the data letter of moment t=k+2
Breath, and carry out the update of magnetic declination when moment t=k+2.
In the measuring process of the subsequent time navigation attitude information, discretization kalman filter method is discretization expansion card
Kalman Filtering method；The measurement of the subsequent time navigation attitude information the following steps are included:
The state equation and measurement equation of discretization are established, expression formula is as follows:
Zk+1=h (Xk+1,k+1)+vk+1=Xk+1+vk+1, (3)
ψm,k+1=αm,k+1+Dk, (7)
Wherein: state vector
Indicate course angle ψ of the carrier coordinate system of current time t=k relative to local horizontal coordinatesk、
Pitching angle thetakAnd roll angleK indicates discrete time point；
The state vector x of function f characterization subsequent time k+1k+1With the state vector x of current time kkBetween relationship；Indicate the time rate of change of angle；Time interval of the dt between t=k and t=k+1；WithGyroscope upward metric data above x, y and z axes after being demarcated respectively in k moment carrier coordinate system；
The quantity of state x of function h characterization subsequent time k+1k+1With measurement zk+1The relationship of the two；Indicate course angle ψ of the carrier coordinate system of subsequent time k+1 relative to local horizontal coordinatesk+1、
Pitching angle thetak+1And roll angleMeasurement；WithRespectively subsequent time k+1 carrier coordinate system
Middle calibration post-acceleration sensor upward metric data above x, y and z-axis；WithUnder respectively
Magnetic Sensor upward metric data above x, y and z-axis after being demarcated in one moment k+1 carrier coordinate system；
WithRespectivelyWithIt is transformed into tri- axis x of geographic coordinate system ll、ylAnd zlOn measured
Data；wkAnd vk+1Respectively systematic procedure noise and measurement noise, statistical property is as follows:
Wherein, k, j indicate that discrete time point, Q are systematic procedure noise covariance matrix, δkjFor Kronecker symbol, R
To measure noise covariance matrix；
Systematic procedure noise w is ignored in settingkWith measurement noise vk+1,
State vector is obtained by equation (1) and (2) and measures the prior estimate of vectorWithIt is expressed as follows:
Wherein,For state vector moment k posterior estimate；
Thus approximate linear state equation and measurement equation are obtained are as follows:
Wherein, Xk+1And Zk+1The respectively true value of state vector and measurement vector in subsequent time k+1；
B is Jacobian matrix of the function f about x local derviation,
W is Jacobian matrix of the function f about w local derviation,
H is Jacobian matrix of the function h about x local derviation,
V is Jacobian matrix of the function h about v local derviation,
One group of complete discretization Extended Kalman filter method iterative process is constructed, is expressed as follows:
Wherein,For the priori covariance matrix of k+1 moment state vector, PkFor the covariance of k moment state vector
Matrix；
The measurement at k+1 moment newly ceasesAre as follows:
In conjunction with equation (4) and (16), can be obtained,
Discretization Extended Kalman filter method measurement updaue equation is as follows:
It enables,
Wherein, (γ1,γ2,γ3) it is the relevant parameter of sensor characteristics, take positive number；
Rk+1=f (η1,η2,η3) R, (19)
Wherein, f (η1,η2,η3) it is (η1,η2,η3) relevant function.
Wherein, KkFor the filtering gain matrix at k moment, PkFor the covariance matrix of the state vector at k moment；
K+1 moment state vector Xk+1It is approximately as described below:
In the measuring process of the subsequent time navigation attitude information, discretization kalman filter method is discretization without mark card
Kalman Filtering method；The measurement of the subsequent time navigation attitude information the following steps are included:
Construct Sigma scatterplot collection:
Wherein,For state vector moment k posterior estimate；PkFor the covariance square of the state vector at k moment
Battle array；N is state vector dimension；λ=α2(n+ κ)-n is the free parameter for obtaining given distribution high-order moment, so that n+ κ=
3,10-4≤ α≤1 represents matrix (n+ λ) Pk-1Subduplicate i-th row or the i-th column；
The time update equation for setting discretization Unscented kalman filtering method is as follows:
Wherein,For state vector moment k+1 priori estimates；For the association of the state vector of moment k+1
The priori estimates of variance matrix；Wi (m)And Wi (c)UT variation calculates the priori estimates of state vector and covariance matrix respectively
Weighted value used；
Wherein, β includes the prior information of state distribution；
In conjunction with equation Rk+1=f (η1,η2,η3) R, f (η1,η2,η3) it is (η1,η2,η3) relevant function, discretization is without mark
The measurement updaue equation of kalman filter method is as follows:
Obtain k+1 moment state vector Xk+1Approximation, it is as follows:
The update of the magnetic biasing angle information the following steps are included:
According to the Posterior estimator course angle of moment k+1With measurement magnetic heading angle αm,k+1, resolve the magnetic biasing of moment k+1
Angle calculates
Magnetic biasing angle information is updated, and stores the declination D of moment k+1k+1。
Beneficial effect
A kind of carrier navigation attitude measurement method updated based on Geomagnetism Information of the invention, is based on adding compared with prior art
Speedometer, gyroscope and Magnetic Sensor measurement data, using the Kalman filtering algorithm of discretization, real-time estimation and update magnetic
Drift angle information, the presence for avoiding the ferrimagnets such as magnetic mineral, reinforcing bar lead to course angle letter caused by magnetic declination variation
Breath distortion and unreliable problem.
The present invention does not depend on the high-precision ground geomagnetic chart prestored, but the navigation attitude measurement side based on Geomagnetism Information real-time update
Method realizes the real time calibration to magnetic declination, to compensate the distortion of extraneous magnetic environment navigation attitude information, reaches and improves navigation attitude measurement
The purpose of reliability and precision.
Detailed description of the invention
Fig. 1 is method precedence diagram of the invention；
Fig. 2 is carrier coordinate system b, local horizontal coordinates l and geographic coordinate system g relation schematic diagram.
Specific embodiment
The effect of to make to structure feature of the invention and being reached, has a better understanding and awareness, to preferable
Examples and drawings cooperate detailed description, be described as follows:
As shown in Figure 1, a kind of carrier navigation attitude measurement method updated based on Geomagnetism Information of the present invention comprising
Following steps:
The first step, initialization: carrier remains static, and based on extraneous input, obtains the course angle of current time t=k
ψkInformation；Based on three axis accelerometer metric data after calibration, the pitching angle theta of current time t=k is obtainedkRoll angleLetter
Breath, calculation formula are as follows:
Wherein, θm,kWithWhen respectively carrier remains static, the pitch angle and roll angle of current time t=k
Measurement information；With3-axis acceleration sensor measures number after calibrating when respectively current time t=k
According to projecting to tri- axis x of carrier coordinate system bb、ybAnd zbOn obtain metric data.
Second step, the calculating of magnetic declination.
Utilize the pitching angle theta of current time t=kkRoll angleInformation, as shown in Fig. 2, by the load of current time t=k
Magnetic Sensor metric data carrier coordinate system b is transformed into local horizontal coordinates l in body sensitive axes, and conversion formula is as follows:
Wherein,WithMagnetic sensor metric data after being calibrated when respectively current time t=k
Project to tri- axis x of carrier coordinate system bb、ybAnd zbOn obtain metric data；WithRespectivelyWithIt is transformed into tri- axis x of local horizontal coordinates ll、ylAnd zlOn obtain metric data.
Thus, it is possible to calculate the measurement magnetic heading angle α of current time t=km,k, calculation formula is as follows:
According to the course angle ψ of current time t=kkWith measurement magnetic heading angle αm,kInformation resolves the magnetic biasing at current time
Angle:
Dk=ψk-αm,k。
Third step, the data acquisition of subsequent time: the accelerometer, gyroscope and magnetic for obtaining subsequent time t=k+1 pass
The metric data of sensor.
4th step, the measurement of subsequent time navigation attitude information.
The pitching angle theta of subsequent time t=k+1 is resolved using discretization kalman filter methodk+1, roll angleAnd boat
To angle ψk+1And measure magnetic heading angle αm,k+1；
The state equation and measurement equation of the Kalman filtering of discretization are established, expression formula is as follows:
Zk+1=h (Xk+1,k+1)+vk+1=Xk+1+vk+1, (3)
ψm,k+1=αm,k+1+Dk,
Wherein: state vectorIndicate the carrier coordinate system of current time t=k
Course angle ψ relative to local horizontal coordinatesk, pitching angle thetakAnd roll angleK indicates discrete time point；
The state vector x of function f characterization subsequent time k+1k+1With the state vector x of current time kkBetween relationship；Indicate the time rate of change of angle；Time interval of the dt between t=k and t=k+1；WithGyroscope upward metric data above x, y and z-axis after being demarcated respectively in k moment carrier coordinate system；
The quantity of state x of function h characterization subsequent time k+1k+1With measurement zk+1The relationship of the two；Indicate course angle ψ of the carrier coordinate system of subsequent time k+1 relative to local horizontal coordinatesk+1、
Pitching angle thetak+1And roll angleMeasurement；wkAnd vk+1Respectively systematic procedure noise and measurement noise, statistical property
It is as follows:
Wherein, k, j indicate that discrete time point, Q are systematic procedure noise covariance matrix, δkjFor Kronecker symbol, R
To measure noise covariance matrix.
As the first embodiment of the invention, when discretization kalman filter method uses Extended Kalman filter
When,
Systematic procedure noise w is ignored in settingkWith measurement noise vk+1,
State vector is obtained by the state equation and measurement equation of the Kalman filtering of discretization and measures the priori of vector
EstimationWithIt is expressed as follows:
Wherein,For state vector moment k posterior estimate；
Thus approximate linear state equation and measurement equation are obtained are as follows:
Wherein, Xk+1And Zk+1The respectively true value of state vector and measurement vector in subsequent time k+1；
B is Jacobian matrix of the function f about x local derviation,
W is Jacobian matrix of the function f about w local derviation,
H is Jacobian matrix of the function h about x local derviation,
V is Jacobian matrix of the function h about v local derviation,
One group of complete discretization Extended Kalman filter method iterative process is constructed, is expressed as follows:
Wherein,For the priori covariance matrix of k+1 moment state vector, PkFor the covariance of k moment state vector
Matrix；
The measurement at k+1 moment newly ceasesAre as follows:
Discretization Extended Kalman filter method measurement updaue equation is as follows:
It enables,
Wherein, (γ1,γ2,γ3) it is the relevant parameter of sensor characteristics, take positive number；
Rk+1=f (η1,η2,η3) R,
Wherein, f (η1,η2,η3) it is (η1,η2,η3) relevant function.
Wherein, KkFor the filtering gain matrix at k moment, PkFor the covariance matrix of the state vector at k moment；
K+1 moment state vector Xk+1It is approximately as described below:
As second of embodiment of the invention, when discretization kalman filter method uses Unscented kalman filtering
When:
Construct Sigma scatterplot collection:
Wherein,For state vector moment k posterior estimate；PkFor the covariance square of the state vector at k moment
Battle array；N is state vector dimension；λ=α2(n+k)-n is the free parameter for obtaining given distribution high-order moment, so that κ=3 n+,
10-4≤ α≤1 represents matrix (n+ λ) Pk-1Subduplicate i-th row or the i-th column；
The time update equation for setting discretization Unscented kalman filtering method is as follows:
Wherein,For state vector moment k+1 priori estimates；For the association of the state vector of moment k+1
The priori estimates of variance matrix；Wi (m)And Wi (c)UT variation calculates the priori estimates of state vector and covariance matrix respectively
Weighted value used；
Wherein, β includes the prior information of state distribution；
In conjunction with equation Rk+1=f (η1,η2,η3) R, f (η1,η2,η3) it is (η1,η2,η3) relevant function, discretization is without mark
The measurement updaue equation of kalman filter method is as follows:
Obtain k+1 moment state vector Xk+1Approximation, it is as follows:
5th step, the update of magnetic biasing angle information.
According to the course angle ψ of subsequent time t=k+1k+1With measurement magnetic heading angle αm,k+1, when updating subsequent time t=k+1
Declination Dk+1；
Dk+1=ψk+1-αm,k+1。
6th step, measurement method continuously carry out: returning to the data acquisition step of subsequent time, obtain moment t=k+2
Data information, and carry out the update of magnetic declination when moment t=k+2.
The basic principles, main features and advantages of the present invention have been shown and described above.The technology of the industry
Personnel are it should be appreciated that the present invention is not limited to the above embodiments, and what is described in the above embodiment and the description is only the present invention
Principle, various changes and improvements may be made to the invention without departing from the spirit and scope of the present invention, these variation and
Improvement is both fallen in the range of claimed invention.The present invention claims protection scope by appended claims and
Its equivalent defines.
Claims (4)
1. a kind of carrier navigation attitude measurement method updated based on Geomagnetism Information, which comprises the following steps:
11) it initializes: obtaining the pitching angle theta of current time t=kk, roll angleWith course angle ψkInformation；
12) it the calculating of magnetic declination: using the Magnetic Sensor metric data of current time t=k, resolves and measures magnetic heading angle αm.k；Root
According to the course angle ψ at current timekWith measurement magnetic heading angle αm,k, calculate declination Dk, calculation formula is as follows:
Dk=ψk-αm,k；
13) data acquisition of subsequent time: the measurement of the accelerometer, gyroscope and Magnetic Sensor of subsequent time t=k+1 is obtained
Data；
14) measurement of subsequent time navigation attitude information: bowing for subsequent time t=k+1 is resolved using discretization kalman filter method
Elevation angle thetak+1, roll angleWith course angle ψk+1And measure magnetic heading angle αm,k+1；
15) update of magnetic biasing angle information: according to the course angle ψ of subsequent time t=k+1k+1With measurement magnetic heading angle αm,k+1, update
Declination D when subsequent time t=k+1k+1；
16) measurement method continuously carries out: returning to the data acquisition step of subsequent time, obtains the data letter of moment t=k+2
Breath, and carry out the update of magnetic declination when moment t=k+2.
2. a kind of carrier navigation attitude measurement method updated based on Geomagnetism Information according to claim 1, which is characterized in that institute
In the measuring process for stating subsequent time navigation attitude information, discretization kalman filter method is discretization Extended Kalman filter side
Method；The measurement of the subsequent time navigation attitude information the following steps are included:
21) state equation and measurement equation of discretization are established, expression formula is as follows:
Zk+1=h (Xk+1,k+1)+vk+1=Xk+1+vk+1, (3)
ψm,k+1=αm,k+1+Dk, (7)
Wherein: state vector
Indicate course angle ψ of the carrier coordinate system of current time t=k relative to local horizontal coordinatesk, pitching
Angle θkAnd roll angleK indicates discrete time point；
The state vector x of function f characterization subsequent time k+1k+1With the state vector x of current time kkBetween relationship；Indicate the time rate of change of angle；Time interval of the dt between t=k and t=k+1；With
Gyroscope upward metric data above x, y and z-axis after being demarcated respectively in k moment carrier coordinate system；
The quantity of state x of function h characterization subsequent time k+1k+1With measurement zk+1The relationship of the two；It indicates
Course angle ψ of the carrier coordinate system of subsequent time k+1 relative to local horizontal coordinatesk+1, pitching angle thetak+1And roll angle
Measurement；WithPost-acceleration sensor is demarcated respectively in subsequent time k+1 carrier coordinate system to exist
Upward metric data above x, y and z axes；WithRespectively subsequent time k+1 carrier coordinate system is got the bid
Magnetic Sensor upward metric data above x, y and z axes after fixed；WithRespectivelyWithIt is transformed into tri- axis x of geographic coordinate system ll、ylAnd zlOn obtain metric data；wkAnd vk+1Respectively
For systematic procedure noise and noise is measured, statistical property is as follows:
Wherein, k, j indicate that discrete time point, Q are systematic procedure noise covariance matrix, δkjFor Kronecker symbol, R is amount
Survey noise covariance matrix；
22) systematic procedure noise w is ignored in settingkWith measurement noise vk+1,
State vector is obtained by equation (1) and (2) and measures the prior estimate of vectorWithIt is expressed as follows:
Wherein,For state vector moment k posterior estimate；
Thus approximate linear state equation and measurement equation are obtained are as follows:
Wherein, Xk+1And Zk+1The respectively true value of state vector and measurement vector in subsequent time k+1；
B is Jacobian matrix of the function f about x local derviation,
W is Jacobian matrix of the function f about w local derviation,
H is Jacobian matrix of the function h about x local derviation,
V is Jacobian matrix of the function h about v local derviation,
23) one group of complete discretization Extended Kalman filter method iterative process is constructed, is expressed as follows:
Wherein,For the priori covariance matrix of k+1 moment state vector, PkFor the covariance matrix of k moment state vector；
The measurement at k+1 moment newly ceasesAre as follows:
In conjunction with equation (4) and (16), can be obtained,
24) discretization Extended Kalman filter method measurement updaue equation is as follows:
It enables,
Wherein, (γ1,γ2,γ3) it is the relevant parameter of sensor characteristics, take positive number；
Rk+1=f (η1,η2,η3) R, (19)
Wherein, f (η1,η2,η3) it is (η1,η2,η3) relevant function.
Wherein, KkFor the filtering gain matrix at k moment, PkFor the covariance matrix of the state vector at k moment；
25) k+1 moment state vector Xk+1It is approximately as described below:
3. a kind of carrier navigation attitude measurement method updated based on Geomagnetism Information according to claim 1, which is characterized in that institute
In the measuring process for stating subsequent time navigation attitude information, discretization kalman filter method is discretization Unscented kalman filtering side
Method；The measurement of the subsequent time navigation attitude information the following steps are included:
31) Sigma scatterplot collection is constructed:
Wherein,For state vector moment k posterior estimate；PkFor the covariance matrix of the state vector at k moment；N is
State vector dimension；λ=α2(n+ κ)-n is the free parameter for obtaining given distribution high-order moment, so that n+ κ=3,10-4≤α
≤ 1, represent matrix (n+ λ) Pk-1Subduplicate i-th row or the i-th column；
32) time update equation for setting discretization Unscented kalman filtering method is as follows:
Wherein,For state vector moment k+1 priori estimates；For the covariance square of the state vector of moment k+1
The priori estimates of battle array；Wi (m)And Wi (c)UT variation respectively calculates used in the priori estimates of state vector and covariance matrix
Weighted value；
Wherein, β includes the prior information of state distribution；
33) equation R is combinedk+1=f (η1,η2,η3) R, f (η1,η2,η3) it is (η1,η2,η3) relevant function, discretization is without mark card
The measurement updaue equation of Kalman Filtering method is as follows:
34) k+1 moment state vector X is obtainedk+1Approximation, it is as follows:
4. a kind of carrier navigation attitude measurement method updated based on Geomagnetism Information according to claim 1, which is characterized in that institute
State the update of magnetic biasing angle information the following steps are included:
41) according to the Posterior estimator course angle of moment k+1With measurement magnetic heading angle αm,k+1, resolve the magnetic declination of moment k+1
It calculates
42) magnetic biasing angle information is updated, and stores the declination D of moment k+1k+1。
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1908584A (en) * | 2006-08-23 | 2007-02-07 | 北京航空航天大学 | Method for determining initial status of strapdown inertial navigation system |
| CN108955671A (en) * | 2018-04-25 | 2018-12-07 | 珠海全志科技股份有限公司 | A kind of Kalman filtering air navigation aid based on magnetic declination, magnetic dip angle |
| CN109163721A (en) * | 2018-09-18 | 2019-01-08 | 河北美泰电子科技有限公司 | Attitude measurement method and terminal device |
| CN109405820A (en) * | 2018-09-05 | 2019-03-01 | 中原工学院 | Unmanned plane navigation attitude monitors system |
| CN109443342A (en) * | 2018-09-05 | 2019-03-08 | 中原工学院 | NEW ADAPTIVE Kalman's UAV Attitude calculation method |
-
2019
- 2019-06-04 CN CN201910480822.7A patent/CN110095115B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1908584A (en) * | 2006-08-23 | 2007-02-07 | 北京航空航天大学 | Method for determining initial status of strapdown inertial navigation system |
| CN108955671A (en) * | 2018-04-25 | 2018-12-07 | 珠海全志科技股份有限公司 | A kind of Kalman filtering air navigation aid based on magnetic declination, magnetic dip angle |
| CN109405820A (en) * | 2018-09-05 | 2019-03-01 | 中原工学院 | Unmanned plane navigation attitude monitors system |
| CN109443342A (en) * | 2018-09-05 | 2019-03-08 | 中原工学院 | NEW ADAPTIVE Kalman's UAV Attitude calculation method |
| CN109163721A (en) * | 2018-09-18 | 2019-01-08 | 河北美泰电子科技有限公司 | Attitude measurement method and terminal device |
Non-Patent Citations (2)
| Title |
|---|
| 朱岩 等: "基于无迹卡尔曼滤波的四旋翼无人飞行器姿态估计算法", 《测试技术学报》 * |
| 陈焕清 等: "EKF和UKF在惯导初始对准中的应用研究", 《长江工程职业技术学院学报》 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111895994A (en) * | 2020-06-29 | 2020-11-06 | 西北工业大学 | Geomagnetic bionic navigation method based on magnetic trend course strategy |
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